Why Standalone Docker Matters: 4 Patterns Every Scalable Architecture Should Consider
This post explores four architecture patterns where standalone Docker is not only justified but recommended.
Causely Feature Demo: Solve the Root Cause of Message Queue Lag
Watch the video to see how Causely turns “Lag High” chaos into confident, informed action in seconds.
Demystifying Automatic Instrumentation: How the Magic Actually Works
Most developers use automatic instrumentation without knowing how it actually works. This post breaks down the key techniques behind it—not to build your own, but to understand what’s really happening when things "just work."
Causely Feature Demo: Pinpointing the Code Change Causing Performance Issues
In this short video, we show how Causely pinpoints the exact code change that triggered cascading performance issues — without requiring you to sift through logs or build custom dashboards.
The Signal in the Storm: Why Chasing More Data Misses the Point
More telemetry doesn’t guarantee more understanding. In many cases, it gives you the illusion of control while silently eroding your ability to reason about the system.
When Everything Is Instrumented, and You Still Don’t Know What’s Broken
In 'Rethinking Reliability for Distributed Systems,' Endre Sara shared a common story: a large-scale customer, running mature microservices in Kubernetes with full observability coverage, still struggles to understand what’s broken during a high-stakes business event.
Causely Feature Demo: Using Ask Causely to Transform Incident Response
In this short demo, we show how Ask Causely shifts incident response from a fire drill to a focused, high-context workflow.
Making Observability Work: From Hype to Causal Insight
A few weeks back, I joined Charity Majors, Paige Cruz, Avi Freedman, Shahar Azulay, and Adam LaGreca for a roundtable on the state of modern observability. It was an honest conversation about where we are, what’s broken, and where things are heading. You can read the full summary on
Causely Feature Demo: Unlock Root Cause Analysis in Grafana
Grafana gives teams the power to visualize everything - but on Day 0, when your dashboards are live and alerts start firing, what your team really needs is clarity. That’s why we built the new Causely plugin for Grafana. In just minutes, Causely connects to your telemetry sources and
Alarm Suppression is Not Root Cause Analysis
“Root Cause Analysis” (RCA) is one of the most overloaded terms in modern engineering. Some call a tagged log line RCA. Others label time-series correlation dashboards or AI-generated summaries as RCA. Some reduce noise by filtering or hiding secondary and cascading alarms. And recently large language models (LLMs) have entered
If Planes Can Fly Themselves Then Why Can’t IT Management be Autonomous?
When it comes to observability and IT operations, our goal should be to get humans out of the loop as much as possible.
From Dashboards to Decisions: Introducing the Causely Plugin for Grafana
With Causely, you can see the why behind what’s happening without having to leave your Grafana interface.